A method of processing digital images by transforming a set of pixels from a three-dimensional space to a normalized two-dimensional space, determining a membership class and membership class level of each pixel in the set of pixels, and selectively modifying colors of pixels in the set of pixels based on the determined membership classes and membership class levels.
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2. The method of claim 1 wherein for each membership class a relative membership value is obtained for a current pixel being processed, a maximum membership value being established in function of the respective membership class, and the membership level being determined in function of a maximum quantized value with a number of bits.
3. The method of claim 1 , further comprising storing in array values of said reference model in correspondence of pairs of values in the normalized two-dimensional space, and of determining the membership level of each pixel by reading from the array a value corresponding to the pair that represents said pixel in the normalized two-dimensional space.
5. The system of claim 4 wherein the means for determining is configured to determine a membership class level for the pixel in each membership class in the set of membership classes and the determined membership class level is a membership class level in the set of membership classes with a highest determined membership class level.
6. The system of claim 4 wherein each class in the set of membership classes is based on a parametric class-membership function that is continuous on the two-dimensional normalized space.
7. The system of claim 4 wherein the means for determining comprises a look-up table.
8. The system of claim 4 wherein the means for determining is configured to apply a Gaussian function to the transformed representation of the pixel.
9. The system of claim 4 , further comprising an image pre-processor coupled to the means for transforming.
11. The chromatic classification device of claim 10 wherein the classification module comprises a Gaussian function generator.
12. The chromatic classification device of claim 10 wherein the classification module is configured to generate the indications using a look-up table stored in the memory.
13. The chromatic classification device of claim 10 wherein the classification module is configured to output a first signal indicative of a membership class associated with respective pixels and a second signal indicative of a membership class level associated with respective pixels and the indications comprise the first signal and the second signal.
14. The chromatic classification device of claim 10 wherein the one or more processing devices comprises discrete circuitry.
15. The chromatic classification device of claim 10 wherein the classification module is configured to classify pixels based on a reference model of classification, the reference model including distinct collections of samples with respective coordinates in the normalized two-dimensional space for each of a number of chromatic classes corresponding to real subjects.
17. The non-transitory computer-readable medium of claim 16 wherein the method comprises: defining a reference model of classification by analyzing a plurality of images of distinct types of subjects, generating distinct collections of samples with respective coordinates in the normalized two-dimensional space for each of a number of chromatic classes corresponding to real subjects, wherein the determining is based on the reference model.
18. The non-transitory computer-readable medium of claim 16 wherein the reference model is defined by a parametric membership function continuous on said normalized two-dimensional space for each of said chromatic classes, parameters of which are determined by processing the collection of two-dimensional samples of each of said chromatic classes.
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January 14, 2013
August 19, 2014
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